1. Field of the Invention
The present invention relates to a track-following control method and a disk apparatus thereof which calculates the control signal for suppressing lead dislocation due to periodic disturbances, such as medium eccentricity by learning control, and executes feed-forward control in a control system to perform feedback control on the moving position of the carriage so that the dislocation amount of the head, with respect to the track center, becomes small (almost zero).
2. Description of the Related Art
A disk apparatus using such a disk as a magnetic disk, optical disk and magneto optical disk as a storage medium is widely used as a memory for images, data and music. In such a disk apparatus, the head must follow the track of the disk to read or write data on the track of the disk. Therefore, track-following control to detect the dislocation of the head from the track and to position the head to the track center is necessary. Recently since the track pitch of a disk is reaching high densities as the storage capacity of the disk increases, periodic disturbance along with the rotation of the disk must be compensated, and for this reason track-following control to compensate for the periodic disturbance is required.
Eccentricity of the disk is generally known as a periodic disturbance, but a periodic disturbance with a frequency higher than an eccentric frequency also exists. In the case of an optical disk unit, for example, in order to improve the track-following performance of the optical beam to the medium track, a double drive type head mechanism is used, which is comprised of a carriage actuator for seek control (also called coarse control) which moves the carriage supported by a sliding bearing section on the stationary-installed guide rail, and a track actuator for tracking control (also called fine control) which moves the optical beam in the direction to cross the track by driving the objective lens mounted on the carriage.
Recently, however, a single drive type head mechanism that has only the carriage actuator, without using the track actuator, is widely used to decrease the cost of the unit. In a single drive type head mechanism, the ball bearing is eliminated from the sliding bearing section so as to decrease the number of parts and to decrease cost.
When such a disk unit is used, that is, when the head mechanism is a single drive type comprised of only the carriage actuator where the ball bearing is eliminated from the sliding bearing section of the carriage, the positioning control of the optical beam on the tracking center based on the tracking error signal is strongly influenced by the solid friction of the carriage bearing section.
FIG. 30 shows the characteristics of solid friction in the single drive type carriage. Here, the moving speed xe2x80x98Vxe2x80x99 and the friction force xe2x80x98Fxe2x80x99 have plus or minus values depending on the moving direction of the carriage. Now consider the case when the moving speed xe2x80x98Vxe2x80x99 of the carriage changes from minus to plus. While the carriage is moving at a moving speed xe2x80x98Vxe2x80x99 with a minus value, the roughly constant kinetic friction force xe2x80x98F1xe2x80x99 is being generated regardless the moving speed. When the moving speed xe2x80x98Vxe2x80x99 of the carriage with respect to the guide rail becomes zero and the carriage begins to move in the opposite direction, a drive force exceeding the static friction force xe2x80x98xe2x88x92F2xe2x80x99 is required, then a roughly constant kinetic friction force xe2x80x98xe2x88x92F1xe2x80x99 is generated.
When the moving speed of the carriage inverts like this, the abrupt change of the friction force acts on the control system as a disturbance, and in order to sufficiently compensate for this disturbance, a feedback control system with a high band is generally required.
The moving speed of the carriage is inverted by the track-following control which periodically compensates the dislocation of the track due to the eccentricity of the disk medium. In other words, when the carriage is controlled so as to follow the eccentricity of the medium, the movement of the carriage with respect to the guide rail is a reciprocating motion synchronizing with the eccentricity period. Therefore the moving speed of the carriage inverts at least twice during a rotation of the medium, and a disturbance due to an abrupt change of the friction force in steps is received each time inversion occurs.
FIG. 29 shows waveform diagrams during track-following under the influence of Coulomb""s friction disturbance, which is an acceleration of the positioner (carriage) for track-following, a change of the friction disturbance, and a waveform of the ideal drive current xe2x80x98I idealxe2x80x99 of the positioner required for track-following, sequentially from the above. The rotation period of the disk is 13.33 ms, and waveforms for three rotation periods of the disk are shown. To simplify description, the static friction factor and the dynamic friction factor are equally xcexc=0.4.
As FIG. 29 shows, in order to implement high precision track following, the ideal drive signal for the positioner should include not only the drive signal for generating the acceleration of the positioner, but also the drive signal that changes abruptly to cancel the friction changes. By a feedback controller, it is difficult to generate such drive signals which include sudden changes because of the limitation of the control band thereof. In other words, a sufficient control band cannot be achieved because of the restriction of the mechanical resonance of the positioner, and as a result, large tracking errors occur.
As FIG. 30 shows, Coulomb friction disturbance, which is a function of the speed of the positioner, can be compensated for using the speed information of the positioner. However, in the case of a disk unit, such as a magneto-optical disk unit, as the velocity information is not obtained with respect to the guide rail due to not have a sensor to measure the location of the positioner with respect to the guide rail, such a compensation cannot be performed. Therefore by considering periodic disturbance synchronizing with disk rotation, feed-forward compensation by learning and obtaining the repetitive disturbance compensation signal is proposed.
As a typical method to compensate such a periodic disturbance, repetitive control is known. In repetitive control, the basic period of a periodic disturbance is divided, for example, by a sampling period of the feedback control system, memory corresponding to each divided period is prepared, and the periodic disturbance is compensated. In a disk unit, such as a magneto-optical disk unit, however, the sampling period of the feedback control system is relatively short. So if the rotation period of the disk is divided by the sampling period, memory length is very long. For example, when the disk rotation frequency is 75 Hz (4500 rpm), the sampling rate is 55 kHz, and memory length is 733. If the resolution of one memory length is 256 bits, a 187 kbit capacity is required.
In order to decrease the memory length, it is possible to set the dividing period of the repetitive control system to a multiple integer of the sampling period of the feedback control system, and skip the feedback information obtained at the sampling period, but learning an accurate feed-forward compensation signal is difficult since feedback information is not effectively utilized.
Therefore the present inventor and others proposed a learning control system where information obtained at the sampling points of the feedback control system can be effectively used for the convergence of learning, even if the sampling frequency of the feedback control system and the dividing period of the learning waveforms (memory length of learning result) are independently set (an example of this is stated in the ASPE (American Society for Precision Engineering) 1999 Meeting paper xe2x80x9cA Precise Track following Control using a Single-stage Tracking Mechanism for Magneto-optical Disk Drive).
This conventional proposal will be described with reference to FIG. 31 to FIG. 33. FIG. 31 is a block diagram of a conventional track-following control system, where a learning control section 101 obtains and stores an unknown function for one rotation of the disk medium as an approximate function by a learning algorithm so that dislocation due to a periodic disturbance becomes almost zero. The learning control section 101 approximates an unknown function for one rotation of the medium to implement dislocation due to a periodic disturbance, such as medium eccentricity synchronizing medium rotation, to be zero, by the height of rectangle C{circumflex over ( )}i of each block (FIG. 33) when the time required for one rotation of the medium is divided by N, and obtains and stores the unknown function as an approximate function.
The learning control section 101, which is between the feedback computing section 100 and the tracking drive section 102, approximates an unknown drive current function Iid (t) which repeats from the start time t=0 to the end time t=TL of one rotation of the medium when the time required for one rotation of the medium is TL as the approximate function I{circumflex over ( )}id (t) by the height of each block C{circumflex over ( )}i having block number i=0xe2x88x92(Nxe2x88x921) when the time required for one rotation of the medium TL is divided by N, and obtains and stores the unknown drive current function as an approximate function I{circumflex over ( )}id(t) by the learning algorithm.
The learning control section 101 comprises a plurality of storage cells which store the height C{circumflex over ( )}i of the rectangular function of each block of the approximate function I{circumflex over ( )}id. The learning control section 101 samples the control signal IFB which is output from the feedback computing section 100, and calculates and updates the height C{circumflex over ( )}i of the rectangular function of each block of the approximate function I{circumflex over ( )}id (t) stored in each storage cell of the memory based on the sampled control signal IFB and the predetermined learning gain Klearn.
And the learning control section 101 reads the height C{circumflex over ( )}i of the rectangular function of each block of the approximate function I{circumflex over ( )}id (t) which was stored in the storage cells of the memory synchronizing with the division period T of the medium rotation, as the learning control signal IFF, adds the learning control signal IFF to the control signal IFB from the feedback computing section 100, and supplies the drive signal IREF to the drive section 102.
According to this learning control section, a stepped friction disturbance compensation signal with high band along with the inversion of the carriage moving direction can be included in the finally obtained learning result, even if it takes some time to converge the learning result, by the low learning gain. By adding this learning control signal to the feedback system by the feed-forward control, the stepped friction disturbance can be eliminated from the feedback control system, track-following errors due to eccentricity of the medium can be decreased even if there is a limitation due to the existence of a higher resonance and even if the control band is low, and the accuracy of on-track control can be improved.
According to prior art, a functional approximation with sufficient accuracy is possible if the number of rectangular functions (that is, memory length) N to be used for a functional approximation is sufficiently large. However, a further decrease in the memory length is demanded. In this case, the number of divisions N must be decreased when the above stepped approximate function is used. If the number of divisions N is decreased, the stepped approximation output cannot be ignored, and when the approximation function is used for the feed-forward compensation signal, the stepped output becomes a disturbance and the track-following accuracy becomes worse.
Since the learning result of the cell corresponding to the learning time of the memory is feed-forward output during the learning of the memory with a phase delay occurring in the feedback control system, and as a result the track-following accuracy drops and the control system in general becomes unstable. For example, when a learning is executed in a system where a disturbance including a relatively high frequency component, such as a stepped disturbance, exists, if the learning result of the cell corresponding to the learning time is feed-forward output, and as a result learning sometimes becomes unstable, and the control system becomes unstable because of the phase delay existing in the feedback control system.
With the foregoing in view, it is an object of the present invention to provide a disk apparatus and a track-following control method thereof to improve the learning accuracy of a periodic disturbance along with the rotation of the disk.
It is another object of the present invention to provide a disk apparatus and a track-following control method thereof to decrease the learning memory length.
It is still another object of the present invention to provide a disk apparatus and a track-following control method thereof to decrease the learning memory length so as to decrease the learning time and to decrease the influence of high frequency noise.
To achieve this object, the track-following control system of the present invention comprises a head which moves to an arbitrary track position of a disk medium, a positional signal detection section which detects a positional signal according to the dislocation amount of the head from a predetermined reference position of the track on the medium, a feedback control section which computes a control signal for moving the head from the positional signal so that the dislocation amount is controlled to zero, a drive section which drives the head based on the control signal, and a learning control section which generates an unknown function for one disk rotation that includes a periodic disturbance stores it in a memory which is comprised of N number of memory cells by a learning algorithm as an approximate function which is approximated by the height of each block when the time required for one rotation of the disk medium is divided by N. The learning control section samples a signal which follows the positional signal according to the learning algorithm at a sampling period which is less than the time obtained by dividing the time required for one rotation of the medium by N, and updates one or more memory cells corresponding to the sampling time synchronized with the sampling period according to the signal value. The learning control section also reads the values of two memory cells located at the cell positions corresponding to the output time at an output period which is less than the time obtained by the time required for one rotation of the medium by N, and interpolates the values of both the memory cells based on the output time, so as to generate a periodic disturbance compensation signal.
According to the present invention, the high-speed memory update rate, the high-speed output rate and the interpolating processing are combined by the learning control section so that the stepped output is prevented, problems due to a feed-forwarding high frequency disturbance by stepped output are prevented, and high precision track-following control can be implemented. Especially with removable medium, such as MO, eccentricity is relatively large compared with HDD, and when such a medium with large eccentricity is used, the discontinuity of the stepped output in the learning result becomes conspicuous (that is, the height difference between the steps becomes conspicuous) because of the increase in the amplitude of the periodic disturbance, so in this case the effect of smoothing by linear interpolation is large.
By combining the learning result output period, which is shorter than the period (TL/N) when the time required for one disk rotation is divided by the memory length N, and the above mentioned linear interpolating processing, very smooth output of periodic disturbance compensation signals is possible, and very accurate track-following control can be implemented.
Since stepped output is prevented, the memory length (number of divisions) can be decreased. In other words, it was demanded to decrease the memory length according to the frequency range (generally at a certain frequency or less) of the periodic disturbance to be suppressed, but in a conventional method, the stepped output problem makes it impossible to decrease the number of divisions to a certain value or less. Therefore in some cases, an unnecessarily high frequency range had to be included in the learning target. If an unnecessarily high frequency component is included in the learning target, the averaging effect on the non-repetitive disturbance decreases, the learning result includes noise, and track-following accuracy drops.
Particularly when the learning operation is performed at a specified position in the radius direction on the medium, and the learning result is feed-forwarded as a fixed value, track-following accuracy may drop since the high frequency periodic disturbance may differ depending on the position in the radius direction, and an effectively learned high frequency periodic disturbance at a location may become a disturbance at another location. In such a case, it is necessary to decrease the number of divisions so as to limit the frequency range to be the target of learning. The present invention can meet such a demand since the memory length (number of divisions) can be decreased considerably compared with prior art.
Also as a secondary effect when the number of divisions is decreased, the averaging effect on unnecessarily high frequency noise improves, and as a result, the high frequency noise included in the learned waveform output is decreased and a higher precision track-following accuracy can be expected. The averaging effect on the anti-periodic high frequency disturbance can also be expected.
As another secondary effect when the number of divisions is decreased, the converging time in learning can be decreased. For example, if the memory length is decreased by half, the converging time required for convergence of learning for the same learning gain can be decreased by half. When disturbance learning is performed for a load sequence after inserting a medium, for example, this secondary effect contributes to decreasing the rise time after disk insertion until access actually becomes possible.
Also according to the present invention, the above mentioned learning algorithm of the learning control section is for calculating the memory cell value after an update by multiplying the sampled signal by a predetermined or variable gain, and adding the computing result to the memory cell value before the update, so high precision learning is possible with a simple algorithm.
Also according to the present invention, the above mentioned learning control section reads the values of the two memory cells at positions associated at a advanced time from the update target memory cell(s) for a predetermined amount of time, and performs interpolating processing for the values of the two memory cells so as to generate a periodic disturbance compensation signal corresponding to the advanced time for the predetermined amount of time. So a time-delay, such as a phase delay of the control target, is considered and the learning result corresponding to a time moved forward is feed-forward output, therefore it is unnecessary to use a phase progress filter. By time-lead compensation for the feed-forward output of the learning result in this way, vibratory fluctuation of a response waveform can be prevented, as in the case without the time-lead compensation, and a stable learning result can be obtained.
According to the present invention, the learning control section samples a signal which follows the position signal, selects two memory cells corresponding to the sampling time as the update target, and updates the values of the memory cells by the learning algorithm, so as to learn the unknown function, therefore learning with higher precision interpolating processing is possible.
Also according to the present invention, the above mentioned learning algorithm of the learning control section changes the update gains for the two memory cells according to the sampling time, and adjusts the update balance between the two memory cells when the two memory cells are updated, so that learning with higher precision interpolating processing is possible.
Also according to the present invention, the above mentioned learning control section samples signals which follow the position signal, updates a value of one of the memory cells, which is allocated to a time close to the sampling time, by the learning algorithm, and learns the unknown function, so that the unknown function can be efficiently learned even if the memory length is decreased, and the calculation amount can be decreased.